24th March 2022
We often talk about early First Notification of Loss (FNOL) reporting and the importance of getting customers to reach out as soon as possible, as it enables claims teams to:
• Support customers when they need it most and identify vulnerable customers who require adjustments
• Deliver the best claims experience to ensure policyholders stay when the policy comes up for renewal
• Ensure validation and liability assessments are completed quickly and easily, flagging potential large losses and instigating mitigation measures to manage the loss
• Get an insight into the claim, suspicious/fraudulent activity is often spotted at FNOL, so early reporting enables teams to investigate early, capturing details and conducting interviews whilst everything is still fresh in everyone’s minds
• Chase any potential third party in a motor claim to minimise credit hire costs
Early reporting is key, but how good is the industry at measuring its own performance in these areas? Most UK insurers do not use conversational analytics to systematically measure performance of customer contact, losing revenues and delivering a less-than-perfect customer experience (CX). In this insight we take a closer look at five insights that have helped leading UK insurers enhance their claims operations to protect indemnity spend and enhance claims journeys.
By using tailored conversational analytics, you can monitor the quality of your FNOL operation. Suspicious activity will automatically flag, ensuring that your team asks the right questions to validate the claim and establish liability. You can see every quality or compliance breach and feed that back to the individual claims handler for coaching and training, as well as flagging high risk compliance failures for follow up action.
In a recent client engagement, when measuring 100% of contacts for quality and compliance using conversational analytics, we highlighted that the insurer failed to act appropriately when a vulnerable customer was detected 20% of the time. One in five vulnerable customers were not being treated as they should have been, in line with the company’s vulnerable customer treatment policy. Additional training on how to treat vulnerable customers was then implemented.
Without the automated quality assurance using conversational analytics, this non-compliance would have been missed as less than one in twenty FNOL contacts were being assessed.
Conversational analytics can act as a second line of defence to capture the details a claims handler may miss. Flagging potential large losses at FNOL, automated conversational analytics enables claims teams to instigate mitigating processes early.
We recently delivered a speech analytics project for a UK insurer where we measured motor accidents involving luxury vehicles or private hire vehicles, as these claims are often expensive. By identifying these potential large losses early, the insurer can seek indemnity or carry out additional processes at the earliest opportunity, limiting the impact of a costly claim.
Conversational analytics is also excellent at tracking how your team is presenting settlement options to customers. By encouraging customers to accept vouchers or using your repair network, insurers can protect claims spend, and it often improves the customer experience too by reducing customer effort.
A UK insurer we worked with implemented near-real-time monitoring of claims settlement conversations with customers and measured how the handlers positioned different settlement offers. One in four handlers opened with the choice of cash or a managed repair, with many customers just selecting cash. The top performing decile of handlers offered just the managed repair option and explained the benefits to the customer, which led to significantly higher revenues.
Conversational analytics can play a big role in fighting fraud as it detects suspicious language at FNOL, automatically altering the system for your investigations team.
A general insurer we worked with had a combination of back-office automated checks and front-office manual checks [by claims handlers] to detect possible fraudulent motor claims. However, they knew that agents were missing a large proportion of the front-office processes. Conversational analytics was deployed to track customer language that should be flagged for potential fraud investigation. The client uncovered c£1.5m in fraudulent cases that were previously missed.
Credit hire costs is a massive challenge for most insurers. With conversational analytics, you can track agent behaviours in capturing details of third parties involved in accidents, enabling your claims team to track the third party down and minimise credit hire costs. Conversational analytics measures if the claims handler asks about third party involvement at FNOL, enabling team leaders to intervene and offer support & coaching should team members fail to comply.
We recently worked with an insurer who wanted to increase its revenue by capturing third party details and offer the third party a repair through its own repair network on fault claims. Conversational analytics measured & reported on how claims teams captured third party details in near-real time. This not only enabled managers to identify who needed additional training and support, but also triggered alerts in real time to enable the re-capture of third-party details if missed at FNOL. This led to a 32% increase in third-party data capture and increased revenues.
To find out how quality assurance and compliance auditing on all claim interactions can help improve your customer experience and protect indemnity spend, please get in touch with our insights and analytics director, Lee Mostari at firstname.lastname@example.org.
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